Purpose Due to the potential risk of inducing cancer, radiation exposure by X‐ray CT
devices should be reduced for routine patient scanning. However, in low‐dose X‐ray CT …

Model-based iterative reconstruction algorithms for low-dose X-ray computed tomography
(CT) are computationally expensive. To address this problem, we recently proposed a deep …

A novel image fusion algorithm based on the nonsubsampled contourlet transform (NSCT) is
proposed in this paper, aiming at solving the fusion problem of multifocus images. The …

High correlation among the neighboring pixels both spatially and spectrally in a
multispectral image makes it necessary to use an efficient data transformation approach …

Recently, deep learning approaches using CycleGAN have been demonstrated as a
powerful unsupervised learning scheme for low-dose CT denoising. Unfortunately, one of …

High-quality computed tomography (CT) images are key to clinical diagnosis. However, the
current quality of an image is limited by reconstruction algorithms and other factors and still …

Multi-scale transform (MST) is an efficient tool for image fusion. Recently, many fusion
methods have been developed based on different MSTs, and they have shown potential …

In this paper, we discuss about applications of different methods for decomposing a signal
over elementary waveforms chosen in a family called a dictionary (atomic representations) …

In this study, we present tool wear prediction system to monitor the flank wear of a cutting
tool by Machine Learning technique namely, Convolutional Neural Network (CNN) …

The multispectral (MS) and the panchromatic (PAN) images belong to different modalities
with specific advantageous properties. Therefore, there is a large representation gap …